A New MSGSA-Optimized Dynamic Window of Spatiotemporal Scan Statistics for Disease Outbreak Detection

The spatiotemporal scan statistics proposed by Kulldorff have been applied to detect numerous disease clusters, and scan statistics based on heuristic algorithm optimization have also been utilized for disease cluster detection. The gravitational search algorithm (GSA) and the recent human mental se...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Haiqi Wang, Haoran Kong, Bin Yan, Liuke Li, Jianbo Xu, Zhihai Wang, Qiong Wang
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Gravitational search algorithm (GSA) mental search scan statistics spatiotemporal anomaly detection spatiotemporal dynamic scanning window Ocean engineering TC1501-1800 Geophysics. Cosmic physics QC801-809
Acceso en línea:	https://doaj.org/article/e3c4d6b674554513b99481c1be9d34fd
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:e3c4d6b674554513b99481c1be9d34fd
record_format	dspace
spelling	oai:doaj.org-article:e3c4d6b674554513b99481c1be9d34fd2021-11-09T00:00:22ZA New MSGSA-Optimized Dynamic Window of Spatiotemporal Scan Statistics for Disease Outbreak Detection2151-153510.1109/JSTARS.2021.3113785https://doaj.org/article/e3c4d6b674554513b99481c1be9d34fd2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9541095/https://doaj.org/toc/2151-1535The spatiotemporal scan statistics proposed by Kulldorff have been applied to detect numerous disease clusters, and scan statistics based on heuristic algorithm optimization have also been utilized for disease cluster detection. The gravitational search algorithm (GSA) and the recent human mental search (HMS) possess superior performance in comparison with several heuristic algorithms, and neither algorithm has yet been applied in spatiotemporal scan statistics. However, the size of the spatiotemporal scanning window utilized in disease applications is constant in the time dimension, and it is difficult to detect changes in the size of an anomalous cluster over time. In this study, we proposed a dynamic cylinder with a variable radius as a spatiotemporal scanning window. In addition, we proposed an improved GSA based on mental search (MSGSA), and the MSGSA was utilized to optimize the dynamic scanning window to detect spatiotemporally anomalous clusters. The performance of the MSGSA was verified on 23 benchmark functions in comparison with the GSA and HMS. Simulated experiments based on the MSGSA and SaTScan showed that the MSGSA-optimized dynamic window yielded better performance based on the obtained accuracies and error rates. Finally, we utilized the MSGSA-optimized dynamic window and other methods to detect spatiotemporally anomalous clusters of hand-foot-and-mouth disease (HFMD) in China (2016) and Guangdong (2009), and the MSGSA-optimized dynamic window yielded better performance on both HFMD datasets. Moreover, the conclusions obtained with the MSGSA-optimized dynamic window were consistent with those of relevant researchers, indicating that the MSGSA possesses certain disease outbreak detection ability.Haiqi WangHaoran KongBin YanLiuke LiJianbo XuZhihai WangQiong WangIEEEarticleGravitational search algorithm (GSA)mental searchscan statisticsspatiotemporal anomaly detectionspatiotemporal dynamic scanning windowOcean engineeringTC1501-1800Geophysics. Cosmic physicsQC801-809ENIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 10821-10834 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Gravitational search algorithm (GSA) mental search scan statistics spatiotemporal anomaly detection spatiotemporal dynamic scanning window Ocean engineering TC1501-1800 Geophysics. Cosmic physics QC801-809
spellingShingle	Gravitational search algorithm (GSA) mental search scan statistics spatiotemporal anomaly detection spatiotemporal dynamic scanning window Ocean engineering TC1501-1800 Geophysics. Cosmic physics QC801-809 Haiqi Wang Haoran Kong Bin Yan Liuke Li Jianbo Xu Zhihai Wang Qiong Wang A New MSGSA-Optimized Dynamic Window of Spatiotemporal Scan Statistics for Disease Outbreak Detection
description	The spatiotemporal scan statistics proposed by Kulldorff have been applied to detect numerous disease clusters, and scan statistics based on heuristic algorithm optimization have also been utilized for disease cluster detection. The gravitational search algorithm (GSA) and the recent human mental search (HMS) possess superior performance in comparison with several heuristic algorithms, and neither algorithm has yet been applied in spatiotemporal scan statistics. However, the size of the spatiotemporal scanning window utilized in disease applications is constant in the time dimension, and it is difficult to detect changes in the size of an anomalous cluster over time. In this study, we proposed a dynamic cylinder with a variable radius as a spatiotemporal scanning window. In addition, we proposed an improved GSA based on mental search (MSGSA), and the MSGSA was utilized to optimize the dynamic scanning window to detect spatiotemporally anomalous clusters. The performance of the MSGSA was verified on 23 benchmark functions in comparison with the GSA and HMS. Simulated experiments based on the MSGSA and SaTScan showed that the MSGSA-optimized dynamic window yielded better performance based on the obtained accuracies and error rates. Finally, we utilized the MSGSA-optimized dynamic window and other methods to detect spatiotemporally anomalous clusters of hand-foot-and-mouth disease (HFMD) in China (2016) and Guangdong (2009), and the MSGSA-optimized dynamic window yielded better performance on both HFMD datasets. Moreover, the conclusions obtained with the MSGSA-optimized dynamic window were consistent with those of relevant researchers, indicating that the MSGSA possesses certain disease outbreak detection ability.
format	article
author	Haiqi Wang Haoran Kong Bin Yan Liuke Li Jianbo Xu Zhihai Wang Qiong Wang
author_facet	Haiqi Wang Haoran Kong Bin Yan Liuke Li Jianbo Xu Zhihai Wang Qiong Wang
author_sort	Haiqi Wang
title	A New MSGSA-Optimized Dynamic Window of Spatiotemporal Scan Statistics for Disease Outbreak Detection
title_short	A New MSGSA-Optimized Dynamic Window of Spatiotemporal Scan Statistics for Disease Outbreak Detection
title_full	A New MSGSA-Optimized Dynamic Window of Spatiotemporal Scan Statistics for Disease Outbreak Detection
title_fullStr	A New MSGSA-Optimized Dynamic Window of Spatiotemporal Scan Statistics for Disease Outbreak Detection
title_full_unstemmed	A New MSGSA-Optimized Dynamic Window of Spatiotemporal Scan Statistics for Disease Outbreak Detection
title_sort	new msgsa-optimized dynamic window of spatiotemporal scan statistics for disease outbreak detection
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/e3c4d6b674554513b99481c1be9d34fd
work_keys_str_mv	AT haiqiwang anewmsgsaoptimizeddynamicwindowofspatiotemporalscanstatisticsfordiseaseoutbreakdetection AT haorankong anewmsgsaoptimizeddynamicwindowofspatiotemporalscanstatisticsfordiseaseoutbreakdetection AT binyan anewmsgsaoptimizeddynamicwindowofspatiotemporalscanstatisticsfordiseaseoutbreakdetection AT liukeli anewmsgsaoptimizeddynamicwindowofspatiotemporalscanstatisticsfordiseaseoutbreakdetection AT jianboxu anewmsgsaoptimizeddynamicwindowofspatiotemporalscanstatisticsfordiseaseoutbreakdetection AT zhihaiwang anewmsgsaoptimizeddynamicwindowofspatiotemporalscanstatisticsfordiseaseoutbreakdetection AT qiongwang anewmsgsaoptimizeddynamicwindowofspatiotemporalscanstatisticsfordiseaseoutbreakdetection AT haiqiwang newmsgsaoptimizeddynamicwindowofspatiotemporalscanstatisticsfordiseaseoutbreakdetection AT haorankong newmsgsaoptimizeddynamicwindowofspatiotemporalscanstatisticsfordiseaseoutbreakdetection AT binyan newmsgsaoptimizeddynamicwindowofspatiotemporalscanstatisticsfordiseaseoutbreakdetection AT liukeli newmsgsaoptimizeddynamicwindowofspatiotemporalscanstatisticsfordiseaseoutbreakdetection AT jianboxu newmsgsaoptimizeddynamicwindowofspatiotemporalscanstatisticsfordiseaseoutbreakdetection AT zhihaiwang newmsgsaoptimizeddynamicwindowofspatiotemporalscanstatisticsfordiseaseoutbreakdetection AT qiongwang newmsgsaoptimizeddynamicwindowofspatiotemporalscanstatisticsfordiseaseoutbreakdetection
_version_	1718441433266913280

A New MSGSA-Optimized Dynamic Window of Spatiotemporal Scan Statistics for Disease Outbreak Detection

Ejemplares similares